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Deciphering the Immune Complexity in Esophageal Adenocarcinoma and Pre-Cancerous Lesions With Sequential Multiplex Immunohistochemistry and Sparse Subspace Clustering Approach.

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cam.issuedOnline2022-05-19
dc.contributor.authorSundaram, Srinand
dc.contributor.authorKim, Eun Na
dc.contributor.authorJones, Georgina M
dc.contributor.authorSivagnanam, Shamilene
dc.contributor.authorTripathi, Monika
dc.contributor.authorMiremadi, Ahmad
dc.contributor.authorDi Pietro, Massimiliano
dc.contributor.authorCoussens, Lisa M
dc.contributor.authorFitzgerald, Rebecca C
dc.contributor.authorChang, Young Hwan
dc.contributor.authorZhuang, Lizhe
dc.date.accessioned2022-06-07T08:12:29Z
dc.date.available2022-06-07T08:12:29Z
dc.date.issued2022
dc.date.submitted2022-02-11
dc.date.updated2022-06-07T08:12:28Z
dc.description.abstractEsophageal adenocarcinoma (EAC) develops from a chronic inflammatory environment across four stages: intestinal metaplasia, known as Barrett's esophagus, low- and high-grade dysplasia, and adenocarcinoma. Although the genomic characteristics of this progression have been well defined via large-scale DNA sequencing, the dynamics of various immune cell subsets and their spatial interactions in their tumor microenvironment remain unclear. Here, we applied a sequential multiplex immunohistochemistry (mIHC) platform with computational image analysis pipelines that allow for the detection of 10 biomarkers in one formalin-fixed paraffin-embedded (FFPE) tissue section. Using this platform and quantitative image analytics, we studied changes in the immune landscape during disease progression based on 40 normal and diseased areas from endoscopic mucosal resection specimens of chemotherapy treatment- naïve patients, including normal esophagus, metaplasia, low- and high-grade dysplasia, and adenocarcinoma. The results revealed a steady increase of FOXP3+ T regulatory cells and a CD163+ myelomonocytic cell subset. In parallel to the manual gating strategy applied for cell phenotyping, we also adopted a sparse subspace clustering (SSC) algorithm allowing the automated cell phenotyping of mIHC-based single-cell data. The algorithm successfully identified comparable cell types, along with significantly enriched FOXP3 T regulatory cells and CD163+ myelomonocytic cells as found in manual gating. In addition, SCC identified a new CSF1R+CD1C+ myeloid lineage, which not only was previously unknown in this disease but also increases with advancing disease stages. This study revealed immune dynamics in EAC progression and highlighted the potential application of a new multiplex imaging platform, combined with computational image analysis on routine clinical FFPE sections, to investigate complex immune populations in tumor ecosystems.
dc.identifier.doi10.17863/CAM.85184
dc.identifier.eissn1664-3224
dc.identifier.issn1664-3224
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337775
dc.languageen
dc.language.isoeng
dc.publisherFrontiers Media SA
dc.publisher.urlhttp://dx.doi.org/10.3389/fimmu.2022.874255
dc.subjectBarrett’s esophagus
dc.subjectesophageal adenocarcinoma
dc.subjectimmune complexity
dc.subjectmultiplex imaging
dc.subjectsparse subspace clustering
dc.subjectAdenocarcinoma
dc.subjectAntigen-Antibody Complex
dc.subjectBarrett Esophagus
dc.subjectCluster Analysis
dc.subjectEcosystem
dc.subjectEsophageal Neoplasms
dc.subjectForkhead Transcription Factors
dc.subjectHumans
dc.subjectImmunohistochemistry
dc.subjectMetaplasia
dc.subjectTumor Microenvironment
dc.titleDeciphering the Immune Complexity in Esophageal Adenocarcinoma and Pre-Cancerous Lesions With Sequential Multiplex Immunohistochemistry and Sparse Subspace Clustering Approach.
dc.typeArticle
dcterms.dateAccepted2022-04-19
prism.publicationNameFront Immunol
prism.volume13
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.versionVoR
rioxxterms.versionofrecord10.3389/fimmu.2022.874255

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